Complex immunogenomic control of serum thyroid hormone levels in fetuses and piglets challenged with Porcine Reproductive and Respiratory Syndrome Virus
Bibliographic record
Abstract
Abstract Porcine Reproductive and Respiratory Syndrome Virus (PRRSV) causes respiratory disease in piglets and reproductive disease in sows. However, the interaction between host immunity and hormone homeostasis is not completely understood but piglet and fetal serum thyroid hormone (i.e., T3 and T4) levels decrease rapidly in response to PRRSV infection. Our objective was to estimate genetic parameters, identify QTL, and uncover nearby candidate genes for T3 and/or T4 levels of piglets and fetuses challenged with PRRSV2. Serum from 5-week old pigs (N=1792) at 11 days post infection (dpi) with PRRSV2 were assayed for T3 levels (piglet_T3). While serum from fetuses (N=1267) at 12 or 21 dpi from sows (N=150) challenged with PRRSV2 in late gestation were assayed for T3 (fetal_T3) and T4 (fetal_T4) levels. Animals were genotyped for 60K or 650K SNPs, heritabilities were estimated and genome wide association studies were performed for each trait separately. We found all three traits to be moderately heritable (18–28%) and the significant QTL (N=37) across several chromosomes collectively explained 24–34% of the genetic variation. A shared QTL identified for all traits on chromosome 6 contained the IL12RB2 and IFI44 genes. The largest QTL identified for both piglet_T3 and fetal_T3 on chromosome 5 contained IL17RA. A large QTL identified for piglet_T3 on chromosome 7 contained 9 MHC genes (e.g., SLA-DMA, SLA-DOA, SLA-DQA, SLA-DRA, and MHC-IA7). In conclusion, our data support the concept that there are complex interactions between thyroid hormone levels and multiple immunogenetic pathways during PRRSV infection, and that there is potential to select for pleiotropic QTL to simultaneously improve host immunity for reproductive and respiratory PRRS.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".